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Record W2900692258 · doi:10.15414/afz.2018.21.02.44-51

Bioaccumulation of macronutrients in herbaceous plants of the Sławno glaciolacustrine plain, northern Poland

2018· article· en· W2900692258 on OpenAlexaboutno aff
Jerzy Jończak, Agniezska Parzych

Bibliographic record

VenueActa fytotechnica et zootechnica/Acta fytotechnica et zootechnica · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotany and Plant Ecology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHerbaceous plantPlantagoBioaccumulationPotassiumPhosphorusChemistryTaraxacum officinaleOrganic matterBotanySoil waterAgronomyAnimal scienceBiologyEnvironmental chemistryDandelionEcology

Abstract

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 Received: 2018-03-24   |   Accepted: 2018-05-29   |   Available online: 2018-06-30 https://doi.org/10.15414/afz.2018.21.02.44-51 The studies aimed to compare bioaccumulation and translocation of macronutrients from roots to above-ground organs for six species of herbaceous plants ( Taraxacum officinale , Rumex acetosa L., Plantago major L., Plantago lanceolata , Potentilla anserina L. and Hypericum perforatum L.) growing in the area of the Sławno Plain, northern Poland. Soil and plant samples were collected in June 2015 from 30 locations (five replications per species) and analysed using standard procedures, including content of nitrogen, phosphorus, potassium, calcium and magnesium. Mean contents of elements in the soil, roots and above-ground organs were calculated based on the results obtained. The content of organic carbon and pH were additionally determined in soil samples. The studied soils have been developed from silty-clayey glaciolacustrine deposits. They were characterised by acid and strongly acid reaction and contained from 9.5 to 28.7 g kg -1 of organic carbon. They were relatively abundant in nitrogen (1.44-1.87 g kg -1 ) and potassium (4.30-5.34 g kg -1 ), whereas poor in phosphorus (0.41-0.57 g kg -1 ), calcium (1.63-2.84 g kg -1 ) and magnesium (3.21-4.08 g kg -1 ). The content of these elements in roots and above-ground parts of the studied plants was usually higher as compared to the soil. It was typical for herbs, reflecting their physiological demands. Only K occurred in higher amounts. The observed contents of nutrients suggest sufficient supply. The lowest bioaccumulation factors in roots were noticed for Hypericum perforatum L. (for N, P, Ca and Mg) or Rumex acetosa L. (for K) and the highest for Plantago major L. (for N, P, K and Ca) or Rumex acetosa L. (for Ca). In above-ground organs weakest bioaccumulation occurred in Hypericum perforatum L. (for K, Ca and Mg), Rumex acetosa L. (for P) or Potentilla anserina L. (for N) and the strongest in Plantago major L. (for N and Ca), Taraxacum officinale (for K and Mg) or Plantago lanceolate (for P). The values of translocation factors from roots to above-ground organs ranged from 1.3 to 3.1 for nitrogen, from 0.8 to 2.0 for phosphorus, from 1.3 to 3.3 for potassium, from 1.1 to 3.7 for calcium and from 1.1 to 3.1 for magnesium. Potassium and calcium were strongly translocated in Taraxacum officinale , whereas nitrogen, phosphorus and magnesium in Hypericum perforatum L. Keywords: herbs, macronutrients, bioaccumulation, translocation, nutrient cycling  References ACHAT, D.L., et al. (2013) Phosphorus status of soils from contrasting forested ecosystems in southwestern Siberia: effects of microbiological and physicochemical properties. In. Biogeosciences , vol. 10, pp. 733–752. doi: https://doi.org/10.5194/bg-10-733-2013 AIRA, M., et al. (2006) C to N ratio strongly affects population structure of Eisenia fetida in vermicomposting systems. In. 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Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.721
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.003
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0040.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.246
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations3
Published2018
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